Smokers' Engagement Behavior on Facebook regarding to Smoking Cessation Verbalization and Facebook Reaction Usage: Content Analysis (Preprint)

BACKGROUND The Transtheoretical Model recommends "processes of change", while the Motivational Interviewing approach offers “motivational language” as indicators of health behavior change. The relationship between these indicators and the usage of Facebook reaction buttons is little known. However, this relationship may highlight how to evaluate one of the most popular engagement indicators (Facebook reactions) in online health behavior change interventions. OBJECTIVE The study aim was to understand the relationship between processes of change, motivational language, Facebook users’ gender, and the Facebook reaction buttons. METHODS A total of 821 comments were analyzed in the current study (N=821), which came from different Facebook users, and responded to image-based, smoking cessation support contents. The processes of change (experiential and behavioral processes) and the motivational language (change talk and sustain talk) in the investigated comments were identified. The presence, the number, and the proportion of these linguistic categories were compared with the Facebook users’ gender and the usage of reaction buttons. RESULTS The Facebook users who used the “Haha” reaction button wrote significantly higher proportion of sustain talk than those who used the “Like” or “Love” reaction (P=.011). No significant difference in the number or proportion of linguistic categories was found between those who used the "Like" reaction button, and those who did not use reaction buttons. The Facebook users who combined the comment and “Love” reaction wrote significantly more change talk than those who used the “Haha” and “Like” reactions, or those who did not utilize these buttons (P<.001). Significant female dominance was observed in the presence, the number, and the proportion of experiential processes and change talk (P<.05). In addition, significant male predominance was found in the presence, the number, and the proportion of sustain talk (P<.05). CONCLUSIONS The "Haha" reaction may be a negative engagement indicator, the "Like" reaction may be a neutral engagement indicator, and the "Love" reaction may be a positive engagement indicator in terms of the smoking cessation during Facebook-based interventions. Furthermore, female engagement may be characterized by utilizing the terms of experiential processes and change talk, while the usage of sustain talk can be typical for male engagement. We recommend the evaluation of processes of change and motivational utterances in participants' comments during online public health interventions.

How to create public health Facebook posts based on Motivational Interviewing a pproach ?

Objective: This research aimed at identifying which types of social media content could achieve higher engagement rate and encourage smokers' motivational language. Intervention contents were classified according to motivational interviewing (MI) strategies. Methods: We categorized the included 701 Facebook posts (N=701) into five different groups according to specific MI strategies. Entertaining and informative strategies were in the control group. Facebook users’ interactions were the primary outcomes (engagement rate, negative feedback, and fan-total reach ratio). The comments reflecting smokers’ motivational language were the secondary outcomes (change talk and sustain talk). Results:MI strategies achieved significantly higher engagement rate, higher fan-total reach ratio, and evoked more change talk. “Elaborating change talk” strategies elicited considerably more change talk. “Affirming change talk” strategies obtained higher fan-total reach ratio and generated significantly more change talk. “Relational MI” strategies achieved significantly higher engagement rate. Conclusions: This study offers an important insight into the Facebook post creating for public health professionals who design Facebook-based interventions. These MI strategies can increase the engagement rate: ”Building Partnership” and ”Expressing Empathy”. These MI strategies can reach more fans: ”Affirming Change Talk” and ”Reflecting Change Talk” strategies. Finally, these MI strategies can support smoking cessation: ”Elaborating Change Talk” and ”Affirming Change Talk” strategies. Source: Pócs D, Óvári T, Watti J, Hamvai Cs, Kelemen O. How to create social media contents based on Motivational Interviewing approach to support tobacco use cessation? A content analysis. Journal of Substance Use 2021; DOI: 10.1080/14659891.2021.1967484. [Full preprint with appendix is available at ResearchGate.]

Active Ingredients and Mechanisms of Change in Motivational Interviewing for Smoking Cessation in Patients With Coronary Artery Disease: A Mixed Methods Study

Background: For patients with coronary artery disease (CAD), smoking is an important risk factor for the recurrence of a cardiovascular event. Motivational interviewing (MI) may increase the motivation of the smokers to stop smoking. Data on MI for smoking cessation in patients with CAD are limited, and the active ingredients and working mechanisms of MI in smoking cessation are largely unknown. Therefore, this study was designed to explore active ingredients and working mechanisms of MI for smoking cessation in smokers with CAD, shortly after a cardiovascular event.Methods: We conducted a qualitative multiple case study of 24 patients with CAD who participated in a randomized trial on lifestyle change. One hundred and nine audio-recorded MI sessions were coded with a combination of the sequential code for observing process exchanges (SCOPE) and the motivational interviewing skill code (MISC). The analysis of the cases consisted of three phases: single case analysis, cross-case analysis, and cross-case synthesis. In a quantitative sequential analysis, we calculated the transition probabilities between the use of MI techniques by the coaches and the subsequent patient statements concerning smoking cessation.Results: In 12 cases, we observed ingredients that appeared to activate the mechanisms of change. Active ingredients were compositions of behaviors of the coaches (e.g., supporting self-efficacy and supporting autonomy) and patient reactions (e.g., in-depth self-exploration and change talk), interacting over large parts of an MI session. The composition of active ingredients differed among cases, as the patient process and the MI-coaching strategy differed. Particularly, change talk and self-efficacy appeared to stimulate the mechanisms of change “arguing oneself into change” and “increasing self-efficacy/confidence.”Conclusion: Harnessing active ingredients that target the mechanisms of change “increasing self-efficacy” and “arguing oneself into change” is a good MI strategy for smoking cessation, because it addresses the ambivalence of a patient toward his/her ability to quit, while, after the actual cessation, maintaining the feeling of urgency to persist in not smoking in the patient.

Language toward Change in Virtual Self-Help Groups Predicts the Abstinence of Problem Gamblers: Automatic Change Talk Classifier (Preprint)

BACKGROUND Although participation in physical meetings has been shown to be effective in reducing the risk of relapse in gambling, the effects of participating in virtual meetings have rarely been reported. OBJECTIVE The present study aims to determine the effectiveness of virtual meetings for problem gamblers. METHODS Participants were 2,828 gamblers participating in the 99 virtual meetings; 360 had stopped gambling for more than three years (abstinent gamblers) and the other 2,468 had not yet stopped gambling (non-abstinent gamblers). Their 1,665,620 utterances were encoded by the automatic change talk classifier. RESULTS The abstinent gamblers participated in the meetings longer than non-abstinent gamblers (t = 8.26, P < .001). They had more change talks than non-abstinent gamblers (t = 6.46, P < .001). The classifier also showed the optimal treatment options responding to minute changes in their participation and utterances in the meetings. CONCLUSIONS Virtual meetings are effective for gamblers. Treatment via the Internet increases the generalizability of treatment because of the size and variety of the data.

Engagement With Motivational Interviewing and Cognitive Behavioral Therapy Components of a Web-Based Alcohol Intervention, Elicitation of Change Talk and Sustain Talk, and Impact on Drinking Outcomes: Secondary Data Analysis

Background Down Your Drink (DYD) is a widely used unguided web-based alcohol moderation program for the general public based on cognitive behavioral therapy (CBT) and motivational interviewing (MI); it provides users with many opportunities to enter free-text responses. Objective The aim of this study was to assess participants’ use of key CBT and MI components, the presence of change talk and sustain talk within their responses, and whether these data are associated with drinking outcomes after 3 months. Methods An exploratory secondary data analysis was conducted on data collected in 2008 from the definitive randomized trial of DYD (N=503). Past week alcohol use at baseline and 3-month follow-up were measured with the TOT-AL. Covariates included baseline alcohol use, age, gender, education level, and word count of the responses. Use of MI and CBT components and presence of change talk and sustain talk were coded by two independent coders (Cohen κ range 0.91-1). Linear model regressions on the subsample of active users (n=410) are presented along with a negative binomial regression. Results The most commonly used component was the listing of pros and cons of drinking. The number of listed high-risk situations was associated with lower alcohol use at 3-month follow-up (Badj −2.15, 95% CI −3.92 to −0.38, P=.02). Findings on the effects of the percentage of change talk and the number of listed strategies to deal with high-risk situations were inconsistent. Conclusions An unguided web-based alcohol moderation program can elicit change talk and sustain talk. This secondary analysis suggests that the number of listed high-risk situations can predict alcohol use at 3-month follow-up. Other components show inconsistent findings and should be studied further.